Mood's Median Test
Computes Mood's median test, a non-parametric test that checks whether several groups share the same median. The idea is simple and robust: you compute the grand median of all the data together and count, in each group, how many values fall above it. If the groups had the same median, those counts would be proportional to the sizes; an imbalance produces a large chi-square statistic. It's quite resistant to outliers, working only with counts. Enter the groups separated by semicolons.
Resultado
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Mood's Median Test
Computes Mood's median test, a non-parametric test that checks whether several groups share the same median. The idea is simple and robust: you compute the grand median of all the data together and count, in each group, how many values fall above it. If the groups had the same median, those counts would be proportional to the sizes; an imbalance produces a large chi-square statistic. It's quite resistant to outliers, working only with counts. Enter the groups separated by semicolons.
Do the groups have the same median?
When you want to compare the center of several groups but distrust the data, because of outliers or strange distributions, comparing means is risky. Mood's median test offers a stripped-down, robust alternative: instead of means, it compares medians, and does so in a way that practically ignores extreme values.
The procedure is almost handmade. You pool all the data and find the grand median. Then, in each group, you count how many values fell above that median and how many below. You build a contingency table from those counts and apply a chi-square test. If all groups had the same median, the proportions above and below would be similar across them; marked differences inflate the statistic.
Enter the groups, with values separated by commas and groups by semicolons. The tool returns the grand median, the chi-square statistic, the degrees of freedom and the p-value. Because it uses only counts of above and below, the test is quite resistant, but also less powerful than alternatives like Kruskal-Wallis when the data are well behaved.
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The results provided by this tool are for general informational and educational purposes only and do not constitute professional, financial, medical, legal, tax or accounting advice. Always confirm important decisions with a qualified professional and official sources.